Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
A Comprehensive Model for Assessing Synergistic Revenue–Cost for the Joint Operation of a Complex Multistakeholder Reservoir System
The joint operation of a multiobjective multistakeholder reservoir system enhances the revenues of downstream-compensated reservoirs at the expense of increasing the operation cost of upstream-compensating reservoirs. Challenges in quantifying the synergistic revenue–cost tradeoffs with incomplete information arise from difficulties in multistakeholder, high-dimensional, and combinational joint optimal operation modeling. This study proposed an equivalent aggregated reservoir multiobjective operation and synergistic revenue–cost assessment model. The proposed methodology includes three parts. Module I constructs revenue indexes covering energy production, water supply, ecological protection, and shipping objectives and uses the maximum outflow change degree as a surrogate “cost” index. Module II defines “aggregated reservoirs” that aggregate upstream reservoirs within the same river system as a single reservoir, reducing model complexity with the least information. Module III evaluates the revenue–cost tradeoffs under various operation scenarios. The following conclusions were derived from a 27-reservoir system: (1) The model complexity was reduced by 67.18% with precision preserved. (2) Key compensating reservoirs are identified via tradeoff curves, which are reservoirs controlling high streamflow with large storage. (3) Upstream compensating reservoirs homogenize the inflows of downstream-compensated reservoirs to increase the downstream synergistic revenue by sacrificing upstream benefit. The proposed method provides a new approach for revenue–cost estimation via the joint optimal operation of a multistakeholder-reservoir system.
A Comprehensive Model for Assessing Synergistic Revenue–Cost for the Joint Operation of a Complex Multistakeholder Reservoir System
The joint operation of a multiobjective multistakeholder reservoir system enhances the revenues of downstream-compensated reservoirs at the expense of increasing the operation cost of upstream-compensating reservoirs. Challenges in quantifying the synergistic revenue–cost tradeoffs with incomplete information arise from difficulties in multistakeholder, high-dimensional, and combinational joint optimal operation modeling. This study proposed an equivalent aggregated reservoir multiobjective operation and synergistic revenue–cost assessment model. The proposed methodology includes three parts. Module I constructs revenue indexes covering energy production, water supply, ecological protection, and shipping objectives and uses the maximum outflow change degree as a surrogate “cost” index. Module II defines “aggregated reservoirs” that aggregate upstream reservoirs within the same river system as a single reservoir, reducing model complexity with the least information. Module III evaluates the revenue–cost tradeoffs under various operation scenarios. The following conclusions were derived from a 27-reservoir system: (1) The model complexity was reduced by 67.18% with precision preserved. (2) Key compensating reservoirs are identified via tradeoff curves, which are reservoirs controlling high streamflow with large storage. (3) Upstream compensating reservoirs homogenize the inflows of downstream-compensated reservoirs to increase the downstream synergistic revenue by sacrificing upstream benefit. The proposed method provides a new approach for revenue–cost estimation via the joint optimal operation of a multistakeholder-reservoir system.
A Comprehensive Model for Assessing Synergistic Revenue–Cost for the Joint Operation of a Complex Multistakeholder Reservoir System
Yufei Quan (Autor:in) / Yang Xu (Autor:in) / Ran Mo (Autor:in) / Xin Huang (Autor:in) / Saijin Ji (Autor:in) / Huili Wang (Autor:in) / Zirui Li (Autor:in) / Bin Xu (Autor:in)
2023
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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